SWIFT-Review vs Universal SLR Assistant

SWIFT-Review is a desktop workbench for formulating systematic reviews and prioritizing literature for screening. Statistical text mining and machine learning identify over-represented topics and rank documents for manual review. Users can search, categorize, prioritize, visualize, and extract information from large citation sets. The ranking workflow requires an initial training seed, and the software does not estimate how many relevant articles remain above a threshold. It can import PubMed IDs or XML, RIS files, and previously saved SWIFT Text-mining Project files; PMID imports retrieve citation data through NLM’s Entrez e-Utilities interface. Exports include Excel, RIS, and plain tab-delimited text. The free desktop software is available for Windows and Mac, with downloads through Sciome’s applications portal after signing in or creating a free account. Installation requires administrative access. The guide lists 64-bit Windows 7, 8, or 10 and 64-bit Mac OS X 10.8 or later, and recommends 8 GB RAM; very large projects may need more. Minor updates usually happen automatically, while major updates may require administrator privileges.

Universal SLR Assistant supports systematic and scoping reviews with AI-assisted screening, extraction, and reproducible outputs. It provides a desktop interface and a browser-based local Web App, and imports RIS, BibTeX, CSV, and plain-text references, including exports from PubMed, Scopus, and Web of Science. Its workflow covers abstract screening, full-text PDF processing, structured extraction, and export; likely duplicates are identified by DOI and fuzzy title matching. Workspace mode stores references, PDF metadata, review items, decisions, and audit events in a local SQLite workspace, separating AI suggestions from human decisions. Exports can include decision files and logs, exclusion reasons, PRISMA-ready counts, a methods disclosure draft, and a manifest. The project supports a range of cloud and local AI providers. Cloud providers receive submitted paper text, while Ollama or another local endpoint can keep it on the user's computer or local network. AI results are assistance only: people must verify them and make final review and reporting decisions. The software is free under the MIT License; cloud AI provider API fees may apply.